Abstract
This paper presents a new computational technique in composite generation and transmission expansion planning considering reliability and cost assessment. The proposed procedure incorporates a virtual database in order to hedging the repetitive calculation by optimisation solver. Since generation and transmission expansion planning is a large scale, mixed-integer, nonlinear and non-convex optimisation task, the proposed technique accelerates the convergence time and reduces computational burden. The composite generation and transmission expansion planning problem is represented as a multi-objective optimisation problem. The virtual database-supported non-dominated sorting genetic algorithm (VDS-NSGA-II) is applied due to comparative assessment potential and good handling of the non-convex problems and non-commensurable objective functions. The virtual database eliminates the repetitive computational efforts in both reliability and hourly operational assessments. In this study, the expected energy not served at hierarchical level II is taken into account as a reliability index, whereas the entire system cost, including annually operational and investment costs, is considered as another objective function. The incidence matrix-based DC optimal power flow is adopted to reflect transmission flow constraint in a framework in which the disconnected bus problem would be handled in both objective functions. To numerically evaluate the efficiency of the proposed method, simulation results on a simple three-bus test system and the modified IEEE 24-bus reliability test system are provided. In spite of huge computation burden at HL-II reliability assessment, the results indicate high efficiency of the proposed VDS-NSGA-II. © 2014 Taylor & Francis.

Abstract

Abstract
This paper analyzes transparent two-TFT current mirrors using a-GIZO TFTs with different mirroring ratios. In order to achieve a high mirroring ratio, the output TFT in the circuit employed a fingered structure layout to minimize area and overlap capacitance. The analysis of the current mirrors is performed in three phases. In the first, a radial basis function based (RBF) model is developed using measured data from fabricated TFTs on the same chip. Then, in the second phase, the RBF model is implemented in Verilog-A that is used to simulate two-TFT current mirrors with different mirroring ratios. The simulations are carried out using Cadence spectre simulator. In the third phase, simulation results are validated with the measured response from the fabricated circuits.

Abstract
Transcriptional regulation plays an important role in every cellular decision. Unfortunately, understanding the dynamics that govern how a cell will respond to diverse environmental cues is difficult using intuition alone. We introduce logic-based regulation models based on state-of-the-art work on statistical relational learning, and validate our approach by using it to analyze time-series gene expression data of the Hog1 pathway. Our results show that plausible regulatory networks can be learned from time series gene expression data using a probabilistic logical model. Hence, network hypotheses can be generated from existing gene expression data for use by experimental biologists.

Abstract
We have developed a framework to support adaptive elements in Web pages. In particular we focus on adaptive menus. Developers are able to define rules for menu adaptation according to the features of the device and browser in use. This paper briefly describes the selected adaptation patterns and their implementation. © Springer International Publishing Switzerland 2014.

Abstract
Cross-border energy markets are becoming more relevant and line congestions may cause significant modifications in their underlined bidding strategies, increasing the market power. This environment requires the development of new tools to measure biased behaviors, and also to try to mitigate them. The related literature makes use of techniques to simulate the bidding strategies, mostly based in optimization models, with or without equilibrium constraints, or mixed complementary problems, and embedded in ad-hoc iterative procedures. This paper presents a model for a two areas system, assuming a conjectural equilibrium. A Mixed Integer Programming method has been implemented to solve the equilibrium conditions, where a binary variable is used to represent the line's power flow status (congested or not) between both two areas. Instead of an ad-hoc algorithm, the Branch and Bound algorithm is used for the resolution, which can assure convergence in specific situations where previous algorithms may diverge. © 2014 IEEE.